code: def to_rgb(
      input_tensor: tf.Tensor,
      kernel_initializer: _KerasInitializer,
      name: Optional[str] = None,
  ) -> tf.Tensor:
      """Converts a feature map to an rgb output.
  
      Args:
        input_tensor: The input feature map.
        kernel_initializer: The kernel initializer to use.
        name: The name of the layer.
  
      Returns:
        The rgb image.
      """
      return keras_layers.FanInScaledConv2D(
          multiplier=1.0,
          filters=3,
          kernel_size=1,
          strides=1,
          kernel_initializer=kernel_initializer,
          padding="same",
          name=name,
      )(input_tensor)
  
file_path: graphics/tensorflow_graphics/projects/gan/architectures_progressive_gan.py
imports: import math
  from typing import Callable, Optional, Sequence, Union
  import tensorflow
  import tensorflow_addons.layers.normalizations
  from tensorflow_graphics.projects.gan import keras_layers
label_desc: Use image node_id 1 for calling a global function with example usage: to_rgb(input_tensor, kernel_initializer, name) and returns: keras_layers